In view of the problem that the AUC value of the recognition result is too low when the currently prevailing i-dentification methods are used to identify power marketing data,which cannot meet the performance requirements of pow-er enterprises for abnormal data recognition,this paper introduces a modified isolation forest algorithm to study the abnor-mal data recognition method of power marketing.By collecting and fusing power marketing data,the features of power marketing data are extracted and decomposed into each modal component.Using the modified isolation forest algorithm,the data anomaly identification is realized.Through comparison experiment,it is proved that the AUC value of the new recognition method is closer to 1 in practical application,which has high identification performance and is worthy of wide application and popularization.
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万方数据
